R help - Oct 2018 - MSE Cross-validation with factor interactions terms MARS regression

Dear R-experts,
I am having trouble while doing crossvalidation with a MARS regression including
an interaction term between a factor variable (education) and 1 continuous
variable (age). How could I solve my problem ?

Here below my reproducible example.

#######

install.packages("ISLR")

library(ISLR)

install.packages("earth")

library(earth)

a<-as.factor(Wage$education)

# Create a list to store the results

lst<-list()

# This statement does the repetitions (looping)

for(i in 1?:200) {

n=dim(Wage)[1]

p=0.667

sam=sample(1?:n,floor(p*n),replace=FALSE)

Training =Wage [sam,]

Testing = Wage [-sam,]

mars5<-earth(wage~age+education+year+age*a, data=Wage)

ypred=predict(mars5,newdata=Testing)

y=Testing$wage

y=Wage[-sam,]$wage

MSE = mean(y-ypred)^2

MSE

lst[i]<-MSE

}

mean(unlist(lst))

summary(mars5)

#######

I did no analysis of your code or thought process, but noticed that you had
the following two successive lines in your code:


y=Testing$wage

y=Wage[-sam,]$wage

This obviously makes no sense, so maybe you should fix this first and then
proceed.

-- Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Mon, Oct 29, 2018 at 1:46 PM varin sacha via R-help <r-help at
r-project.org>
wrote:
>
> Dear R-experts,
> I am having trouble while doing crossvalidation with a MARS regression
> including an interaction term between a factor variable (education) and 1
> continuous variable (age). How could I solve my problem ?
>
> Here below my reproducible example.
>
> #######
>
> install.packages("ISLR")
>
> library(ISLR)
>
> install.packages("earth")
>
> library(earth)
>
> a<-as.factor(Wage$education)
>
> # Create a list to store the results
>
> lst<-list()
>
> # This statement does the repetitions (looping)
>
> for(i in 1 :200) {
>
> n=dim(Wage)[1]
>
> p=0.667
>
> sam=sample(1 :n,floor(p*n),replace=FALSE)
>
> Training =Wage [sam,]
>
> Testing = Wage [-sam,]
>
> mars5<-earth(wage~age+education+year+age*a, data=Wage)
>
> ypred=predict(mars5,newdata=Testing)
>
> y=Testing$wage
>
> y=Wage[-sam,]$wage
>
> MSE = mean(y-ypred)^2
>
> MSE
>
> lst[i]<-MSE
>
> }
>
> mean(unlist(lst))
>
> summary(mars5)
>
> #######
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
	[[alternative HTML version deleted]]

Hi Bert,

Many thanks, I have fixed it but it still don't work... . 
Best,






Le lundi 29 octobre 2018 ? 22:07:26 UTC+1, Bert Gunter <bgunter.4567 at
gmail.com> a ?crit :





I did no analysis of your code or thought process, but noticed that you had the
following two successive lines in your code:


y=Testing$wage

y=Wage[-sam,]$wage

This obviously makes no sense, so maybe you should fix this first and then
proceed.

-- Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Mon, Oct 29, 2018 at 1:46 PM varin sacha via R-help <r-help at
r-project.org> wrote:
> 
> Dear R-experts,
> I am having trouble while doing crossvalidation with a MARS regression
including an interaction term between a factor variable (education) and 1
continuous variable (age). How could I solve my problem ?
> 
> Here below my reproducible example.
> 
> #######
> 
> install.packages("ISLR")
> 
> library(ISLR)
> 
> install.packages("earth")
> 
> library(earth)
> 
> a<-as.factor(Wage$education)
> 
> # Create a list to store the results
> 
> lst<-list()
> 
> # This statement does the repetitions (looping)
> 
> for(i in 1?:200) {
> 
> n=dim(Wage)[1]
> 
> p=0.667
> 
> sam=sample(1?:n,floor(p*n),replace=FALSE)
> 
> Training =Wage [sam,]
> 
> Testing = Wage [-sam,]
> 
> mars5<-earth(wage~age+education+year+age*a, data=Wage)
> 
> ypred=predict(mars5,newdata=Testing)
> 
> y=Testing$wage
> 
> y=Wage[-sam,]$wage
> 
> MSE = mean(y-ypred)^2
> 
> MSE
> 
> lst[i]<-MSE
> 
> }
> 
> mean(unlist(lst))
> 
> summary(mars5)
> 
> #######
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>